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Cake day: July 14th, 2024

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  • Less about customizations and more just it doing what i want, and not doing things i don’t want. When you build it all from the ground up then you don’t have surpise bloat or walls to work around/within.

    But most of my customizing from what people use probably would be around my dev environments. Things like rebuilding python libraries to support my gpu are fairly trivial in arch when i need to deviate from releases available through package managers (aur/pypi). Another thing was setting up my data science environments to share some core libraries but venv the rest.

    It’s a hard question to answer though because fundamentally I’m just using the computer how i want to use it. When you say customization it sounds like you are expecting me to do things differently than other people and really it’s just like i said earlier-- doing things i want it to do, and not doing things i don’t want it to do. And I’m not really sure what walls other people are stuck behind for me to know what I’m doing differently. I just find a problem, fix it, and move on











  • Expired domains first can be bought by registrars and then they might sell or auction it off. For instance godaddy will scoop up a lot of domains and auction them off even if it was registered somewhere else first. And unfortunately a surname.tld probably will invite domain squatters to try to get it and then charge much more for it

    You can look into something like dropcatch which they will try to get the domain for you before another registrar gets it. Look into their backorder service and just check the timing to make sure they still can try to get it.

    Regularly check the whois info (via icann lookup) to see which registrar currently has it which can help you determine if it has gone to an auction.





  • There are cuda packages for arch. I can confirm they work.

    https://wiki.archlinux.org/title/GPGPU

    Edit- to add i haven’t found arch’s limit, it feels like i am bound only by my own limit in my time, ability, and willingness to tinker with my setup. arch itself is widely supported, it has many official packages through pacman, and then additional through the “arch user repository” (AUR) so chances are most of the things you want or need have a package that can be installed with an AUR helper (like yay/paru which install from both pacman and AUR). In other distros you get more of a one-size fits all and you lose some of that ability to change things whereas arch you’re giving a minimal setup and left to build the system to your liking. It does take more time and expertise than other distros but it does give you more control. For me the trade off was an easy decision, but it’s not something i blanket recommend to everyone.




  • Tflops is a generic measurement, not actual utilization, and not specific to a given type of workload. Not all workloads saturate gpu utilization equally and ai models will depend on cuda/tensor. the gen/count of your cores will be better optimized for AI workloads and better able to utilize those tflops for your task. and yes, amd uses rocm which i didn’t feel i needed to specify since its a given (and years behind cuda capabilities). The point is that these things are not equal and there are major differences here alone.

    I mentioned memory type since the cards you listed use different versions ( hbm vs gddr) so you can’t just compare the capacity alone and expect equal performance.

    And again for your specific use case of this large MoE model you’d need to solve the gpu-to-gpu communication issue (ensuring both connections + sufficient speed without getting bottlenecked)

    I think you’re going to need to do actual analysis of the specific set up youre proposing. Good luck